This invention relates to a time series pattern generating system for generating a time series pattern relating to an operation processing order from an event log in which event records recorded with the processing history of a plurality of operations constituting a business process are arranged in chronological order.
In recent years, demand for improvements in business efficiency, security and so on has increased together with the need to obtain a detailed understanding of business process conditions. In response to these needs, BAM (business activity monitoring) has been proposed as a technique for understanding business process conditions from a server side using a workflow system. In BAM, business process conditions are learned by recording and analyzing an operation processing history in accordance with a workflow that defines a processing order of operations constituting a pre-registered business process and dependence relationships therebetween. In addition to the operations defined in the workflow, however, an actual business is executed in conjunction with spreadsheet or plotting applications and so on that cannot be monitored on the server side, and therefore, with BAM alone, business process conditions cannot be understood accurately.
To solve this problem, a method of recording the processing history of the business at the business venue has been proposed. In a technique disclosed in JP 2002-107473 A, for example, a recording application is installed on a terminal used for the business by an operator. At the start time and end time of each operation of each business process, the operator operates the recording application to input a business process name, an operation name, job identification information, and start/end times, and records these items as an event record. An event log is then generated by arranging the recorded event records in chronological order. With the technique disclosed in JP 2002-107473 A, business process conditions can be recorded in this manner.
However, with the technique disclosed in JP2002-107473, only a method of recording an event log is disclosed, and therefore a technique for analyzing an event log including an extremely large number of recorded event records is required.
Hence, JP 2006-004346 A discloses a technique for determining an order relationship between two event records included in an extremely large event log from a start time and an occurrence probability, and extracting an occurrence pattern of the event record by combining the obtained relationships.
Further, JP 2005-062963 A discloses a technique for classifying event records hierarchically, and extracting and displaying a time series pattern, which indicates the frequent occurrence of relationships between event records on each tier of the hierarchy, from a start time and an occurrence probability.